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- W1759790807 abstract "Compressive Sampling Matching Pursuit(CoSaMP) and Subspace Pursuit(SP) are popular compressive sensing greedy recovery algorithms. In this letter, we demonstrate that the CoSaMP algorithm can successfully reconstruct a $K$-sparse signal from a compressed measurement ${bf y}={bf A x}$ by a maximum of $5K$ iterations if the sensing matrix ${bf A}$ satisfies the Restricted Isometry Constant (RIC) of $delta_{4K} < frac {1}{sqrt{5}}$ and SP algorithm can reconstruct within $6K$ iteration when RIC of $delta_{3K} < frac {1}{sqrt{5}}$ is satisfied. The proposed bound in convergence with respect to number of iterations shows improvement over the existing bounds for Subspace Pursuit and provides new results for CoSaMP." @default.
- W1759790807 created "2016-06-24" @default.
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- W1759790807 date "2014-04-19" @default.
- W1759790807 modified "2023-09-27" @default.
- W1759790807 title "On the number of iterations for convergence of CoSaMP and SP algorithm." @default.
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